Time-Series Clustering for Portfolio Diversification

In this tutorial, we will explore the concept of time-series clustering and how it can be used for portfolio diversification. Portfolio diversification is a strategy that aims to reduce risk by investing in a variety of assets that are not highly correlated with each other. By clustering time-series data, we can identify groups of assets that exhibit similar patterns over time, allowing us to construct diversified portfolios.

Photo by Andras Vas on Unsplash

To demonstrate this concept, we will use financial data from real assets such as JPMorgan Chase (JPM), Goldman Sachs (GS), Morgan Stanley (MS), BlackRock (BLK) and Citigroup ©. We will download the data using the yfinance library, which provides an easy way to access historical financial data from Yahoo Finance.

Installing Required Libraries

Before we begin, let’s install the necessary libraries. Open your terminal and run the following command:

pip install yfinance numpy pandas matplotlib scikit-learn

Make sure you have an active internet connection to download the required data.

Importing Required Libraries

Let’s start by importing the required libraries for our analysis. Run the following code:

import yfinance as yf…